59results about How to "Good noise canceling effect" patented technology

The invention discloses an X-ray compound tomoscanning imaging system and method. The whole imaging system consists of a mechanical device (comprising a shooting box, an X-ray linear array detector, an X-ray bulb tube, a light concentrator, a lifting rotating shaft and a table surface) and a monitoring feedback control system. The method comprises the steps of firstly setting the frame number N of a sequence image needed by super-resolution reconstruction; performing total body X-ray scan on a monitored object to obtain an X-ray planar image; horizontally moving the small distance of a sub-detection unit by the detector until an image sequence of displacements of N frames of sub-pixels is obtained; acquiring an X-ray planar image with a high resolution in a super-resolution reconstructionimage sequence, and finding out an interested point in the image; rotationally tomoscanning the interested point in the fault which the interested point is positioned at so as to reconstruct a computed tomography (CT) image; horizontally moving the small distance of the sub-detection unit by the detector until the image sequence of displacements of N frames of sub-pixels displacement is obtained;and super-resolution reconstructing the image sequence to obtaining the CT image with a high resolution in the super-resolution reconstruction image sequence.

The invention relates to a full-wave magnetic resonance signal random noise abatement method combining EMD and TFPF algorithms. The method is a 'blind' filtering method in which filtering range designis not needed. The method comprises the steps of firstly utilizing decomposition characteristics of the EMD algorithm to decompose full-wave magnetic resonance signals into different intrinsic mode functions, then using the TFPF algorithm to code signal dominant mode functions into instantaneous frequencies of unit amplitude analytic signals, and utilizing the characteristic that time-frequency distribution of the analytic signals is concentrated along instantaneous frequency to inhibit random noise. The full-wave magnetic resonance signal random noise abatement method combining the EMD and TFPF algorithms has the advantages that few filtering constraint conditions are needed, the operation is simple, there is no need to design a filtering range in a time-frequency domain, and the methodhas high adaptability to full-wave magnetic resonance signals with a low signal-noise rate; the detection efficiency is remarkably improved, a good denoising effect can be obtained only through once measuring, random noise is effectively reduced, signal components are not lost at the same time, the signal-to-noise ratio can be remarkably increased, and the accuracy of later inversion is improved.

The invention relates to a magnetic resonance three-component noise removing device. The magnetic resonance three-component noise removing device is formed through a structure. The structure is characterized in that an upper computer is connected with a transmitting coil through a control system, a transmitting circuit and a resonance matching capacitor; the transmitting circuit is connected with a power supply; the control system is connected with a receiving coil and a reference coil respectively through an A / D (Analog to Digital) collection and amplification circuit and a conditioning circuit. The magnetic resonance three-component noise removing device is applicable to a detection area with complex and changeable environment noise and uneven space distribution of the noise; due to the adoption of relevance between x-component signals, y-component signals and z-component signals which are sensed by coils paved in the same detection place, the z-component noise is removed, then filtered and processed to obtain reliable magnetic resonance signals, so that the wiring space is greatly saved and the processing result is flexible and accurate; in particular, when sharp-peak noise with great amplitude exists, the noise removing effect is excellent. Through the magnetic resonance three-component noise removing device, the influence of strong electromagnetic interference near the cities, the villages and the water-deficient areas is eliminated, and the problem of limited application of a nuclear magnetic resonance underground water detection method is solved.

The invention discloses a harmonic wavelet frequency domain extraction and vibration source identification method for a weak vibration signal. The method adopts harmonic wavelet transformation to realize frequency domain extraction and time domain reconstruction on the weak vibration signal, and realizes frequency domain extraction of a weak periodic vibration signal in the strong noise background. The invention also provides a vibration signal source identification method based on the coherence function analysis. The vibration signal source identification method comprises the following steps of: firstly judging the independent number of signal sources on the whole frequency band, then detecting whether important signals are missed or not, and finally respectively identifying the independent and non-independent conditions; for the non-independent signal sources, providing a filter method for carrying out priority ordering; and after carrying out priority ordering, detecting whether the important signal sources are missed or not by using a multiple coherence function, and then respectively identifying the independent signal sources and the non-independent signal sources by using a coherence function and a partial coherence function. By adopting the scheme, the weak vibration signal can be accurately detected, and the vibration sources can be effectively identified.

The invention discloses an OFDM signal bandwidth blind estimating method which includes the following steps. Firstly, a received OFDM signal undergoes Welch changing and a power spectrum is obtained. Secondly, the obtained power spectrum undergoes EMD decomposition and multiple IMF components are obtained. Thirdly, a threshold lambda of IMF variance contribution rate is set. IMF components of which the IMF variance contribution rates are smaller than lambda are removed. By means of reserved IMF components, filtering and noise abating are performed and an OFDM signal power spectrum is reconstructed. Fourthly, a differential of the reconstructed power spectrum is worked out. Positions of the maximum value and the minimum value of an impulse are abstracted and respectively serve as a starting point and a closing point of an OFMD signal passband and a differential value of the maximum value and the minimum value is the width of the passband so that the width of the OFDM signal is estimated. Fifthly, multiple circulation times are set, the previous four steps are repeated and an average statistics value of the bandwidth is estimated and serves as an estimated value of a precise bandwidth of the OFMD signal.

The invention discloses a rubbing acoustic emission denoise method based on empirical wavelet transform. The method comprises the following steps that (1) an acoustic emission signal is acquired through a rubbing acoustic emission experimental device; (2) adaptive partition is performed on the acoustic emission signal according to the Fourier spectrum features; (3) a wavelet window is added after partition, and an empirical scale function and an empirical wavelet function are defined; (4) empirical wavelet transform is defined; and (5) wavelet denoising is performed on each empirical mode component fi and then reconstruction is performed based on EWT. The beneficial effects of the rubbing acoustic emission denoise method based on empirical wavelet transform are that adaptive partition is performed according to the Fourier spectrum of the acoustic emission signal, and a wavelet filter bank is constructed to extract different intrinsic mode components included in the acoustic emission signal so that less modes are decomposed and the phenomena of mode aliasing and endpoint effect can be effectively filtered; and wavelet denoising is performed on each empirical mode component, reconstruction is performed based on EWT and denoising is performed on the signal so that the denoised signal has high signal-to-noise ratio and the denoise effect is obvious.

The present invention provides a gas concentration prediction method based on an adaptive modularization neural network, and relates to the mine gas concentration detection technology field. The method comprises: collecting the gas concentration data, storing the gas concentration data in a gas concentration database, performing adaptive noise removing processing of the gas concentration data in the database to take the gas concentration data after the adaptive noise removing processing as chaotic time series, establishing the training sample set of an adaptive modularization neural network, constructing an adaptive modularization neural network soft measurement prediction model, and predicating the gas concentration by employing the constructed predication model according to the newly obtained gas concentration data and the historical data in the gas concentration database. The gas concentration prediction method based on the adaptive modularization neural network has a significant noise removing effect, can retain the useful information in the gas concentration time sequence while effectively removing the noise and can construct the soft measurement predication model of the adaptive modularization neural network, and the input information is integrally processed through a plurality of different submodels so as to improve the learning precision and the generalization performance of the predication model and improve the robustness of the prediction model.

The invention discloses an active noise reduction system and method used for a tower type air purifier. The noise reduction system comprises a noise detection device, a noise reduction unit and a noise removing device; the noise detection device comprises a microphoneand a vibration sensor; the noise reduction unit comprises an analog-digital conversion circuit, a feedforward filter and a digital-analog conversion circuit; the noise removing device is a loudspeaker; the active noise reduction method comprises the steps that the microphone and the vibration sensor are used for detecting a noise signal and a vibration signal; according to the signals, the transmission characteristic of the noise is determined, according to the noise transmission characteristic, the feedforward filter is designed, a noise removing signal is obtained from the noise signal and the vibration signal through the feedforward filter, and the loudspeaker plays the noise removing signal to achieve noise removing. According to the active noise reduction method for the tower type air purifier, the good noise reduction effect can be obtained, and the air purifier purifies indoor polluted air and meanwhile sends out little noise.

An active noise-eliminating earphone comprises a shell, a horn disposed in shell, an external microphone disposed outside of the shell. A controller is connected between the horn and the external microphone, and stores a characteristic related function; external microphone receives external noise message which passes through controller and be processed by characteristic related function in the controller; the horn emits anti-noise signal; external noise signal transmits to shell and counteracts with anti-noise signal emitted by the horn. Only a microphone installed outside of shell can achieve noise-eliminating function, which reduces cost and size, and the effect for eliminating noise is obvious, response time is short, and noise-eliminating efficiency is promoted. The invention also comprises a noise-eliminating method of active noise-eliminating earphone.

The invention relates to a de-noising method for an electric vibration signal of a wind driven generator and a storage medium. The method comprises the following steps: decomposing the vibration signal of the wind driven generator into a group of modal components through a variational modal decomposition algorithm; respectively calculating a multi-scale permutation entropy value of each modal component; judging whether the multi-scale permutation entropy value of each modal component exceeds a preset entropy value or not; if the multi-scale permutation entropy exceeds the preset entropy, performing noise reduction processing on the modal components with the multi-scale permutation entropy exceeding the preset entropy; and combining and reconstructing the modal component subjected to the noise reduction processing and the modal component not subjected to the noise reduction processing to obtain a vibration signal subjected to the noise reduction processing. Vibration signals are denoised through combination of variational mode decomposition and multi-scale permutation entropy, signal distortion can be effectively reduced, and the denoising effect is good.

The invention discloses a noise reduction method and a handheld mobile terminal. The method is applied to a first handheld mobile terminal. An answering module is arranged in the first handheld mobile terminal. A first audio playing unit is arranged in the answering module, and the first audio playing unit is used for playing a first voice signal sent by a second handheld mobile terminal when the first handheld mobile terminal communicates with the second handheld mobile terminal. At least one second audio playing unit is arranged on the answering module. The method comprises the following steps: collecting a first related parameter of the first voice signal; generating a second voice signal provided with a second related parameter based on the first related parameter, wherein the second related parameter of the second voice signal is matched with the first related parameter; and outputting the second voice signal through the at least one second audio playing unit to reduce noise of the first voice signal.

The invention relates to a horn, in particular to an integrated minitype noise reduction horn. The integrated minitype noise reduction horn comprises a microphone, and a horn unit, the horn unit comprises a circular horn support, a circular magnetic path and a circular vibration film. A round hole is arranged at the center of the circular horn support and connected with the microphone in an embedded mode, and the centers of the microphone, the circular horn support, the circular magnetic path and the circular vibration film are arranged on the same axis. The horn unit and the microphone adopt an integrated design, space of a noise reduction unit can be effectively reduced, and thickness of a cavity of an ear shell can be reduced, and the direction of the microphone of picking up the noise reaches a best angle to enable the integrated minitype noise reduction horn to be good in noise reduction effect, and due to the characteristics and advantages of the integrated minitype noise reduction horn, the integrated minitype noise reduction horn can be applied to products like a head-wearing type noise reduction headset and the like.

The invention relates to a wearable voice recognition endoscope control system, which comprises endoscope equipment, wearable equipment which can worn before eyes and a processing terminal which is connected to the endoscope equipment and the wearable equipment, wherein the endoscope equipment comprises an in vivo camera unit, an image information processing unit and a first image input unit; the wearable equipment comprises an optical display unit and a communicating unit; and the processing terminal comprises a microprocessing unit as well as a memory unit, a transmission unit and a power supply unit connected to the microprocessing unit. By virtue of the wearable equipment which is arranged before glasses, the wearable voice recognition endoscope control system disclosed by the invention can display images recorded by a conventional endoscope before the eyes in the form of a virtual large screen, and moreover, an operation and control system, which is capable of conducting a series of actions including operating, taking pictures, shooting camera, operating and controlling and the like on the endoscope in accordance with a voice command, is provided.

The invention relates to a video face recognition method based on wavelet transformation and a neural network algorithm, belongs to the technical field of face recognition, and is divided into a dataprocessing part and a face recognition part. According to the method, firstly, data processing is carried out, that is, denoising processing is carried out on a face image through wavelet transformation, then face image features are extracted through wavelet transformation, and then dimensionality reduction of feature data is achieved through a self-organizing neural network. When face recognitionis carried out, a BP neural network is trained by using part of sample data, and then the trained BP neural network is used to carry out face image recognition. According to the invention, on the premise of ensuring that the recognition accuracy is higher than 99.95%, the recognition speed on the mobile terminal is less than 80ms, so that the mobile terminal device has an accurate and rapid facerecognition function.

The invention relates to the technical field of heat pump units, and discloses a double-compressor cold water heat pump unit. The double-compressor cold water heat pump unit comprises double compressors, an evaporator, a condenser and a throttling valve, wherein cooling fins are arranged at the lower end of the condenser, four sets of cushioning mechanisms are fixedly arranged at the lower ends ofthe cooling fins, a cooling device is arranged on the outer side of the bottom of the cushioning mechanisms, a rain collecting device is arranged above the interior of a heat dissipation pool, a dirtremoving mechanism is arranged at the front end of the cooling device and the interior of the cooling device, and spraying devices are connected to the positions, located in front of and behind the condenser, in the cooling device; and the cooling device comprises the heat dissipation pool, a water discharging pipe and fans, the water discharging pipe is fixedly arranged on one side of the upperend of the heat dissipation pool, and the four sets of fans are arranged at the corners of the top of the inner side of the heat dissipation pool. According to the double-compressor cold water heat pump unit, the effect of buffering and protecting the heat pump unit can be achieved, the service life of the heat pump unit is prolonged, and the noise generated by the heat pump unit is reduced.

The invention discloses a brain wave medical record signal reduction method based on three-layer cross game energy trees, the brain wave medical record signal reduction method includes designing two adjacent three-layer cross game trees Ti and Tj, realizing self game in a same main layer and cross coordinated game among different main layers, and adopting a depth-first search strategy to select global optimization elites Elitisti-c and Elitistj-c; distributing elite energy gain matrix PMENnxn to optimal elite, and enhancing performance, on acquiring self-adaptive Nash energy exploration and development balance, of elite on the main layers; realizing cross game energy reduction of brain wave medical record signals, and enabling the optimal elite driven by elite energy vector Gamma to converge to optimal Nash balance points of each main layer to realize brain wave medical record signal reduction accuracy balance so as to output global optimal brain wave medical record signals. By the brain wave medical record signal reduction method, brain wave medical record signal reduction efficiency can be improved effectively, and an important method is provided for brain wave noise elimination and feature extraction and analysis; the brain wave medical record signal reduction method has high application value in brain disease diagnosis and adjuvant therapy.

The invention discloses a denoising method and device. The denoising method comprises the steps that the microphones of external sound pickup equipment and terminal equipment connected with the external sound pickup equipment are applied to acquire sound wave signals of the environment; the acquired sound wave signals are analyzed, and primary path signals and secondary path signals are determined; and the primary path signals and the secondary path signals act as input signals to perform denoising processing, and the denoising processing result acts as output signals to be outputted. With application of the denoising method and device, the finally determined primary path signals and the secondary path signals are enabled to be maintained to be close in noise signals and further different in voice signals so that a better denoising effect can be obtained.

The invention provides a Lamb wave signal denoising method based on a John Saris model and fractional differentiation. The method overcomes the defects in the prior art, and the signal to noise ratio of denoised signals is increased. The method includes the steps that various-order fractional differentiation is conducted on a Lamb wave signal amplitude spectrum containing noise, John Saris distribution is used as a model of the amplitude spectrum to be processed, a cubic relation between a fractional differentiation maximum value and a zero crossing point of the John Saris model amplitude spectrum and a differential order is provided, a calculation formula of characteristic parameters of the amplitude spectrum is built to extract characteristic parameters and rebuild an amplitude spectrum of original signals, and then denoised Lamb wave signals are reconstructed by the combination of a phase spectrum.

The invention relates to the digital image processing technology, and discloses a method for eliminating high light sensitivity speed noise and digital image processing equipment. In the invention, multi-order multi-resolution decomposition is carried out on each color channel of the digital image with high ISO speed noises, the high frequency part decomposed in each order is filtered, and each color channel is rebuilt by inverse decomposition. By judging and eliminating high ISO speed noises under multiple resolutions instead of within a certain window range, the noise elimination effect is obviously improved; and moreover, each pixel adaptive window is free of dynamic adjustment, thus omitting the process for calculating the signal statistical properties in quantity, thereby greatly reducing the operation complexity of noise elimination and facilitating implementation in portable or embedded systems.

The invention discloses a pulse interval-based pulse image sensor noise elimination method and device, applied to a pulse pixel structure; the method comprises the steps: obtaining a first pulse interval, caused by uniform illumination, of a pixel and a second pulse interval, under a dark condition, of the pixel in consideration of time domain noise and space domain noise; obtaining a dark currentcoefficient matrix; carrying out dark current non-consistency correction on the pulse matrix containing the noise by utilizing the dark current coefficient matrix to obtain a pulse matrix after darkcurrent correction, then carrying out guided filtering for multiple times to obtain a noise matrix, subtracting the noise matrix from the pulse matrix after dark current correction to obtain a denoised pulse matrix, and completing noise elimination. The method has the advantages that the pulse data is directly processed and the processing mode is simple and effective, so that the method has the potential of being implemented on hardware.

The invention provides an electromagnetic valve switch control method and system and an air conditioner, and relates to the field of air conditioner electromagnetic valve switch control. The electromagnetic valve switch control method aims at solving the problem that customer use is affected due to the fact that existing air conditioner switch components produce large noises when turned off or turned on. The electromagnetic valve switch control method comprises the steps that whether an on-off controller sends a turn-off or turn-on signal to an electromagnetic valve switch or not is detected, and when the turn-off or turn-on signal is detected, the current of an electromagnetic coil in the on-off process of the electromagnetic valve switch is controlled by adjusting the voltage to produce gradual gentle or segmented step type changes. The specific implementation mode of the electromagnetic valve switch control method comprises the step that the duty ratio of a control signal in the turn-off or turn-on process of the electromagnetic valve switch is adjusted, and then the current of the electromagnetic coil is adjusted. According to the electromagnetic valve switch control method and system and the air conditioner, the duty ratio of the control signal in the on-off process of the electromagnetic valve switch is adjusted, so that the change mode of the current in the electromagnetic valve coil is converted from hopping to gradual gentle, the electromagnetic force can be changed gently, the impulsive force magnitude is reduced, and noises caused by collision are effectively reduced.

The invention relates to a magnetorheological fluid inflatable vibration reducer. The magnetorheological fluid inflatable vibration reducer comprises a working cylinder, a piston rod inserted in the working cylinder and capable of performing a reciprocating motion, a piston module arranged at a free end of the piston rod, and a floating piston and a sealed gas chamber arranged below the piston module in sequence; the piston module divides an inner cavity of the working cylinder above the floating piston into a first working cavity and a second working cavity; both the first working cavity and the second working cavity are filled with magnetorheological fluid; the piston module includes a piston fixedly connected with the free end of the piston rod, a magnet exciting coil wound on the outer side wall of the piston, and circulating valves inserted through the piston; the magnetorheological fluid is circulated between the first working cavity and the second working cavity through the circulating valves; and the sealed gas chamber is filled with high-pressure gas. Compared with the prior art, the magnetorheological fluid inflatable vibration reducer is excellent in sealing effect, largely accelerates relative speeds of the piston module and the working cylinder, can generate high enough damping force, is excellent in noise eliminating effect, is high in magnet exciting utilization rate, and is low in energy consumption.

The invention provides an active noise elimination device for a cabinet type case, which structurally comprises a case noise collecting microphone, an error monitoring and correcting microphone, an active noise elimination loudspeaker and a control module, wherein the control module is composed of a main processor DSP, an audio encoder, an audio conditioning circuit, a processor power adapter and a loudspeaker power supply. According to the invention, a noise source, which is collected by the noise collecting microphone in the active noise elimination device, of the cabinet type case is enabled to act as a reference, and noises are counteracted through anti-noise signals which are generated by the active noise elimination loudspeaker according to real-time feedback of a monitoring error of the error monitoring and correcting microphone by using an existing LMS adaptive algorithm technology, wherein the anti-noise signals and noise signals collected by the noise collecting microphone are identical in frequency but opposite in amplitude. By using the active noise eliminating device, noises, which are generated by rotation of a cooling fan, vibration of a cabinet body and the like, of the cabinet type case can be greatly reduced, and noise pollutions of a work environment are reduced.

The invention discloses an intelligent identification method of an underground working face operation type based on gas concentration parameter. The method comprises the steps of firstly obtaining thegas concentration data of a working face from a mine safety monitoring system, and storing in a gas parameter database, processing the gas concentration data in the database by adaptive noise reduction filter, and then establishing the historical gas concentration data sample set on the basis of the classification of operation types and the extraction of sensitive characteristic parameters, and constructing the adaptive modular rough neural network prediction model, and identifying the corresponding operation types by using the constructed prediction model. The method of the invention has obvious noise reduction effect, can effectively remove noise while retaining the effective information in the gas concentration time series, can realize analysis and identification of the working type ofthe working face, and can better realize the depth mining and the secondary utilization of the gas concentration data.

The invention discloses a low-electromagnetic-noise miniature direct-current motor and a manufacturing method thereof, and particularly relates to a miniature direct-current motor capable of effectively reducing noise and electromagnetic interference and a manufacturing method of the miniature direct-current motor. The low-electromagnetic-noise miniature direct-current motor comprises a motor device, a filtering device and a shielding ring device. The motor device comprises a stator assembly, a rotor assembly and a cover plate assembly. The filtering device comprises a network consisting of aninductor and a capacitor, is arranged at the lead end of the cover plate, and prevents an electromagnetic disturbance signal from being conducted and input into the motor; the shielding ring device is an isolation ring formed by stamping a galvanized steel sheet and is wrapped on the casing. The miniature direct-current motor, the filtering device and the shielding device are combined for use, noise caused by disturbance signals conducted and input to the motor by a power supply is eliminated or weakened, an internal magnetic field is prevented from diffusing outwards or an external magneticfield is prevented from entering, and interference is reduced.

The invention discloses a rotary separating valve. The rotary separating valve comprises an upper casing, wherein a separating static sheet is arranged in the upper casing, a nitrogen exhausting opening is formed in the center of the separating static sheet, a rotating movable sheet is arranged on the separating static sheet, and a nitrogen exhausting passage is formed in the rotating movable sheet; one end of the nitrogen exhausting passage communicates with a molecular tower, and the other end of the nitrogen exhausting passage communicates with the nitrogen exhausting opening; an only-out-no-in one-way valve is arranged at the nitrogen exhausting opening. The invention discloses a method for prolonging the service life of an oxygen generator. The rotary separating valve is mounted in the oxygen generator, when a machine does not work, the one-way valve has a sealing effect, so that greasy dirt and humid air in the outside cannot enter a nitrogen storing cavity and the molecular tower through the nitrogen exhausting opening to be in contact with a molecular sieve, the service life of the molecular sieve is prolonged, and further the service life of the oxygen generator is prolonged; when the machine works, the one-way valve is opened, the nitrogen exhausting function of the machine is met, and sealing and nitrogen exhausting functions can be realized at the same time. The rotary separating valve and the method for prolonging the service life of the oxygen generator disclosed by the invention have the advantages that the rotary separating valve is simple in structure and ingenious in conception, and the service life of the oxygen generator is effectively prolonged.

The invention discloses a particle swarm principle-based power distribution network data preprocessing method adopting big data clustering, and belongs to the field of power distribution network reliability prediction. For the normalized power distribution network data, a clustering number selection mechanism which takes a bending moment method as a main method and takes a concave-convex coefficient method is adopted as an auxiliary method to obtain an optimal clustering number of a sample; after clustering analysis is carried out on the samples, abnormal value identification standards of upper and lower critical graphs are adopted to delimit diagnosis thresholds; if the distance between the sample and the clustering center is greater than a diagnosis threshold,a judgment is made that thesample is an outlier sample and removed. further, de-noised sample data is obtained; Potential rule of the power distribution network fault is predicted by adopting the sample data subjected to de-noising. Not only is the defect that a bending moment method and a concave-convex coefficient algorithm are easy to fall into a local extreme value overcome, but also global optimization of a particle swarm algorithm is maintained, and convergence speed of a bending moment method and a concave-convex coefficient algorithm is relatively high; the invention has the advantages of being good in denoisingeffect and high in sorting accuracy and effectiveness.

The invention discloses a front lower sway arm assembly which comprises a lower sway arm body assembly (1). The lower sway arm body assembly (1) is provided with a ball head assembly (2), a front bushing (3) and a rear bushing (4), a sway arm (16) is arranged between the ball head assembly (2) and the front bushing (3), the rear bushing (4) is internally provided with an outer sleeve (14) and an inner sleeve (15) arranged in the outer sleeve (14), an annular rubber body (17) is arranged between the outer sleeve (14) and the inner sleeve (15), and the annular rubber body (17) is provided with a pair of limiting holes (18) which are symmetrical about the center of the inner sleeve (15). According to the front lower sway arm assembly, the requirement on the bearing capacity after the material is changed can be met, transmission mechanisms of a transmission shaft and the like can be avoided, the weight is the lightest, the cost is low, the universality is good, noise cannot be generated by friction between the rear bushing and a frame, and the service life of the rear bushing is long.